title: Brain coordination dynamics: true and false faces of phase synchrony and metastability.
abstract: Understanding the coordination of multiple parts in a complex system such as the brain is a fundamental challenge. We present a theoretical model of cortical coordination dynamics that shows how brain areas may cooperate (integration) and at the same time retain their functional specificity (segregation). This model expresses a range of desirable properties that the brain is known to exhibit, including self-organization, multi-functionality, metastability and switching. Empirically, the model motivates a thorough investigation of collective phase relationships among brain oscillations in neurophysiological data. The most serious obstacle to interpreting coupled oscillations as genuine evidence of inter-areal coordination in the brain stems from volume conduction of electrical fields. Spurious coupling due to volume conduction gives rise to zero-lag (inphase) and antiphase synchronization whose magnitude and persistence obscure the subtle expression of real synchrony. Through forward modeling and the help of a novel colorimetric method, we show how true synchronization can be deciphered from continuous EEG patterns. Developing empirical efforts along the lines of continuous EEG analysis constitutes a major response to the challenge of understanding how different brain areas work together. Key predictions of cortical coordination dynamics can now be tested thereby revealing the essential modus operandi of the intact living brain.
authors.affiliation: Human Brain and Behavior Laboratory, Center for Complex Systems and Brain Sciences, Florida Atlantic University, 777 Glades Road, Boca Raton, FL 33431, USA. tognoli@ccs.fau.edu
authors.forename: Emmanuelle
authors.initials: E
authors.lastname: Tognoli
authors.forename: J A Scott
authors.initials: JA
authors.lastname: Kelso
mesh_terms: D000818:Animals; D001921:Brain / Q000502:physiology*; D004569:Electroencephalography; D006801:Humans; D008959:Models, Neurological; D009434:Neural Pathways / Q000502:physiology; D017711:Nonlinear Dynamics; D011597:Psychomotor Performance / Q000502:physiology*